Why AI Strategy Needs To Start with Leadership, Not IT

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The Uncomfortable Truth About AI Failure

Here's a stat that should make every executive pause: 42% of companies abandon their AI initiatives before they ever reach production (S&P Global, 2025).

And shockingly, that number has more than doubled from just a year ago.

With organisations pouring billions into AI, why are so many projects failing? The technology is proven. The use cases are clear. The ROI is compelling.

So what's going wrong?

The problem isn't your technology. It's your approach.

Why Starting with IT Is Setting You Up to Fail

Most organisations treat AI the same way they treated their last software upgrade:

• Hand it to IT
• Set a budget
• Wait for results

This is exactly why projects fail.

A recent MIT Sloan Management Review study found a revealing statistic: 91% of data leaders say cultural challenges are blocking their AI efforts. Only 9% point to technology issues (MIT Sloan, 2025).

Nine out of ten obstacles to AI success have nothing to do with the technology itself.

Yet most companies are still treating AI as a technical problem.

The Real Challenge: Culture, Not Code

AI isn't like other technology implementations. It's not only about upgrading your systems, it's about fundamentally changing how your organisation works.

We talk about 'everything everywhere always at once' - that means AI affects all business units, every level, all workflows, and now.

It is a powerful resource that changes workflows. And It requires people to work differently with machines. It demands new skills.

None of that is an IT problem. It's a people problem.

And people problems need leadership solutions.

Research from Harvard Business School puts it perfectly: "AI won't replace humans, but humans with AI will replace humans without AI" (Harvard Business School, 2025).

The question is: who's preparing the humans in your organisation for this shift?

IT? Or your leadership team?

What's Actually Working: The Leadership-First Approach

Here's the good news: we now have data on what works.

Organisations that get AI right do three things differently:

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1. They Put Leaders in Charge (Not Just IT)

A 2024 industry survey found that 52% of successful organisations now use cross-functional teams of business and technology leaders to drive AI strategy. Just a year ago, only 5% were doing this (Slalom, 2024).

Why? Because they realised AI decisions can't be made based only on technology.

You need:

• Operations leaders who understand workflows
• HR leaders who can manage workforce changes
• Finance leaders who drive ROI
• Strategy leaders who align with business goals
• And yes, IT leaders who implement the technology

2. They Start with Culture, Then Add Technology

Companies with strong AI-focused change leadership see 3.2x higher profit margins than those using traditional IT-led approaches (McKinsey, 2025).

The difference? They don't ask "What can this technology do?"

They ask "How does this change how we work and how do we prepare our people for that change?"

3. They Get CEO-Level Buy-In from Day One

When surveyed, 77% of CIOs and 60% of CEOs say they're jointly driving AI transformation (EY CIO Sentiment Survey, 2024). Not IT alone. Not business alone. Together.

This dual leadership model works because it combines technical expertise with strategic authority and cultural change management.

The Gap Between IT and Leadership

Here's the disconnect: Only 28% of CIOs say leading transformation is their top priority, even though 85% are expected to be change makers (Foundry's State of the CIO Survey, 2024).

Why? Because most of their time is consumed by operational IT functions, keeping systems running, handling security etc.

They simply don't have the bandwidth to drive organisation-wide cultural transformation. And truthfully, it's not their primary skill set.

Cultural transformation requires:

• Managing widespread resistance and fear
• Communicating vision across all levels
• Aligning diverse stakeholders
• Changing ingrained behaviours
• Building psychological safety for experimentation

These are leadership competencies, not technical ones.

Five Steps to Start Your AI Strategy the Right Way

1. Move AI Ownership to the C-Suite

Your CEO needs to own AI strategy the same way they own overall business strategy. This isn't a project to delegate, it's a transformation that requires top-level authority.

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2. Build Your Cross-Functional AI Team

Bring together leaders from:

• Business operations
• Human resources
• Finance
• Strategy
• Technology

Give them real authority and accountability for AI outcomes.

3. Invest in Change Management First

Before you buy more AI tools, invest in preparing your organisation. Companies that integrate proper change management see 47% higher success rates with AI initiatives (WTW Research, 2024).

This means:

• Clear communication about AI's role
• Training programmes for affected roles
• Support for career transitions
• Open dialogue about concerns and fears

4. Build Leadership AI Fluency

Your executives don't need to code. But they do need to understand:

• What AI can and can't do
• How it will change their departments
• What new risks it introduces
• How to identify good use cases

Create executive education programmes focused on AI strategy, not technical details.

5. Start Small, But Start Strategic

Don't begin with your biggest, boldest AI vision. Start with a strategic vision that:

• Has clear business value
• Affects multiple departments
• Requires cultural change
• Tests your leadership's ability to drive adoption

Learn from that before scaling.

The Bottom Line

Your AI strategy's success isn't determined by which tools you buy or how sophisticated your models are.

It's determined by whether your leadership team can drive the cultural transformation AI demands.

Research shows this clearly: organisations are treating AI deployment as a technology problem rather than a business transformation challenge (S&P Global, 2025). And that's why they're failing.

The companies winning with AI aren't the ones with the best tools. They're the ones with the best leadership.

They understand that AI is fundamentally about change, and change requires leaders, not just technicians.

The question isn't whether your organisation will adopt AI. The question is whether your leadership is ready to drive the transformation it requires.

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The first step to change

This is where The AI Institute comes in. Our courses are designed to help leaders, teams, and organisations build the mindset and capability to thrive in the age of AI.

Whether you’re developing an organisation-wide strategy through AI Core, upskilling your marketing team with AI Marketing, or empowering every employee to work smarter with Copilot, our courses turn theory into actionable transformation.

Because AI isn’t just about integrating new technology, it’s about reimagining how your people work, make decisions, and lead change.

Start building an AI-fluent culture today.

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👉 Explore our courses and bring AI leadership to your organisation with The AI Institute.

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References: 

MIT Sloan Management Review (2025). "Why AI Demands a New Breed of Leaders." Based on Foundry's 2024 State of the CIO survey of hundreds of IT leaders. https://sloanreview.mit.edu/article/why-ai-demands-a-new-breed-of-leaders/

Harvard Business School (2025). "AI-First Leadership: Embracing the Future of Work." 2025 Global Leadership Development Study. https://www.harvardbusiness.org/insight/ai-first-leadership-embracing-the-future-of-work/

S&P Global (2025). "The AI Implementation Paradox: Why 42% of Enterprise Projects Fail Despite Record Adoption." Analysis of AI project success and failure rates. https://medium.com/@stahl950/the-ai-implementation-paradox-why-42-of-enterprise-projects-fail-despite-record-adoption-107a62c6784a

WTW (2024). Research on change management effectiveness in AI implementations. https://www.virtasant.com/ai-today/ai-readiness-assessment

McKinsey & Russell Reynolds Associates (2025). "Why Most AI Transformations Fail Before They Start." Based on CEO AI Labs Roundtables research. https://www.russellreynolds.com/en/insights/articles/why-most-ai-transformations-fail-before-they-start

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